Reduction System Research Articles

Structured query language query join optimization by using rademacher averages and mapreduce algorithms

Query optimization involves identifying and implementing the most effective and efficient methods and strategies to enhance the performance of queries. This is achieved by intelligently utilizing system resources and considering various performance metrics. Table joining optimization involves optimizing the process of combining two or more tables within a database. Structured query language (SQL) optimization is the progress of utilizing SQL queries in the possible way to achieve fast and accurate database results. SQL optimization is critical to decreasing the no of queries in research description framework (RDF) and the time for processing a huge number of relatable data. In this paper, four new algorithms are proposed such as hash-join, sort-merge, rademacher averages and mapreduce for the progress of SQL query join optimization. The proposed model is evaluated and tested using waterloo sparql diversity test suite (WatDiv) and lehigh university benchmark (LUBM) benchmark datasets in terms of time execution. The results represented that the proposed method achieved an enhanced performance of less execution time for various queries such as Q3 of 5362, Q8 of 5921, Q9 of 5854 and Q10 of 5691 milliseconds. The proposed gives better performance than other existing methods like hybrid database-map reduction system (AQUA+) and join query processing (JQPro).

Combined Computational and Experimental Study Reveals Complex Mechanistic Landscape of Brønsted Acid-Catalyzed Silane-Dependent P═O Reduction.

The reaction mechanism of Brønsted acid-catalyzed silane-dependent P═O reduction has been elucidated through combined computational and experimental methods. Due to its remarkable chemo- and stereoselective nature, the Brønsted acid/silane reduction system has been widely employed in organophosphine-catalyzed transformations involving P(V)/P(III) redox cycle. However, the full mechanistic profile of this type of P═O reduction has yet to be clearly established to date. Supported by both DFT and experimental studies, our research reveals that the reaction likely proceeds through mechanisms other than the widely accepted "dual activation mode by silyl ester" or "acid-mediated direct P═O activation" mechanism. We propose that although the reduction mechanisms may vary with the substitution patterns of silane species, Brønsted acid generally activates the silane rather than the P═O group in transition structures. The proposed activation mode differs significantly from that associated with traditional Brønsted acid-catalyzed C═O reduction. The uniqueness of P═O reduction originates from the dominant Si/O═P orbital interactions in transition structures rather than the P/H-Si interactions. The comprehensive mechanistic landscape provided by us will serve as a guidance for the rational design and development of more efficient P═O reduction systems as well as novel organophosphine-catalyzed reactions involving P(V)/P(III) redox cycle.

Single-atom catalysis for advanced oxidation and reduction systems in water decontamination

Single-atom catalysis for advanced oxidation and reduction systems in water decontamination

Photocatalytic CO2 reduction of CuO-Zn1-xCuxO (ZCO)/Ti3C2Tx MXene heterojunctions with enhanced interfacial charge transfer

Photocatalytic CO2 reduction reaction (CO2RR) synthesis of recycled fuel is a promising pathway to assist the mitigating fossil fuel depletion. Finding efficient and inexpensive high performance CO2RR semiconductor photocatalysts is a giant challenge in the field of photocatalytic reduction. This work constructs the novel-designed interfacial Schottky junction of CuO-Zn1-xCuxO (ZCO)/Ti3C2Tx via electrostatic spinning and electrostatic self-assembly techniques. The catalysts exhibit tight contact heterogeneous interface companies with enhanced CO2 chemisorption capability and proved by various characterizations for efficient carrier separation and migration capacity. The optimized ZCO/Ti3C2Tx nanosheet composites significantly improved their photocatalytic performance. The best samples yielded 5.855 and 2.518 μmol g−1 h−1 of CO and CH4, which are 6 and 1.73 times higher than the conversion of ZCO, respectively, and maintain stability after four cycles without the use of sacrificial agents. In addition, the mechanism and reaction pathways of the photocatalytic process are proposed through In-situ diffuse reflectance Infrared Fourier Transform Spectroscopy (In-situ DRIFTS) and X-ray absorption near edge structure (XANES) analysis. This work provides a new semiconductor/co-catalyst system for the photocatalytic reduction of CO2 and demonstrates that Ti3C2Tx MXene is a hopeful and inexpensive co-catalyst.

Charge Transport Approaches in Supramolecular Systems Composing of Semiconductor and Molecular Metal Complex for Photocatalytic Reduction of CO2.

The design of photocatalytic supramolecular systems composing of semiconductors and molecular metal complexes for CO2 reduction has attracted increasing attention. The supramolecular system combines the structural merits of semiconductors and metal complexes, where the semiconductor harvests light and undertakes the oxidative site, while the metal complex provides activity for CO2 reduction. The intermolecular charge transfer plays crucial role in ensuring photocatalytic performance. Here, we review the progress of photocatalytic supramolecular systems in reduction of CO2 and highlight the interfacial charge transfer pathways, as well as their state-of-the-art characterization methods. The remaining challenges and prospects for further design of supramolecular photocatalysts are also presented.

A Numerical Study on Dust Control: Evaluating the Impact of Spray Angle and Airflow Speed in the Coalescence of Droplets and Dust

Spray dust reduction is one of the most economical and effective technologies for controlling coal dust in coal mining faces. We aimed to reproduce a spray dust reduction process in a simulation and investigate the mechanism by which the spray angle and airflow speed influence the dust reduction effect. Based on the DPM (discrete phase model) and the mixture model, we constructed a spray dust reduction evaluation model by considering two-way momentum coupling between the discrete phase and the continuous phase. The results showed that installing nozzles near the dust source (coal mining drum) significantly reduced the dust concentration at the coal mining face from 0.0005 kg/m3 to 0.0001 kg/m3. The increase in airflow speed and spray angle enhanced the horizontal transportation of droplets and dust, providing opportunities for the droplets to condense the dust; however, if the droplets have too large an angle, this will result in an insufficient concentration of droplets in the vicinity of the dust source. When the spray angle is 45°, increasing the airflow speed provides a better dust reduction effect. The nozzle position should also be set scientifically according to the airflow speed. Based on simulation results, a mathematical calculation model of spray dust reduction efficiency was constructed. These results can guide the key parameters of spray dust reduction systems, such as the installation position of the nozzle, the spray angle, and the airflow speed. This paper provides ideas for simulating spray dust reduction for other dust types.

The fundamental theorem of calculus in differential rings

In this paper, we study the consequences of the fundamental theorem of calculus from an algebraic point of view. For functions with singularities, this leads to a generalized notion of evaluation. We investigate properties of such integro-differential rings and discuss many examples. We also construct corresponding integro-differential operators and provide normal forms via rewrite rules. They are then used to derive several identities and properties in a purely algebraic way, generalizing well-known results from analysis. In identities like shuffle relations for nested integrals and the Taylor formula, additional terms are obtained that take singularities into account. Another focus lies on treating basics of linear ODEs in this framework of integro-differential operators. These operators can have matrix coefficients, which allow to treat systems of arbitrary size in a unified way. In the appendix, using tensor reduction systems, we give the technical details of normal forms and prove them for operators including other functionals besides evaluation.

Synthesis of core–shell silicon–carbon nanocomposites via in-situ molten salt-based reduction of rice husks: A promising approach for the manufacture of lithium-ion battery anodes

Silicon (Si) has gained substantial interest as a potential component of lithium-ion battery (LIB) anodes due to its high theoretical specific capacity. However, conventional methods for producing Si for anodes involve expensive metal reductants and stringent reducing environments. This paper describes the development of a calcium hydride (CaH2)–aluminum chloride (AlCl3) reduction system that was used for the in-situ low-temperature synthesis of a core–shell structured silicon–carbon (Si–C) material from rice husks (RHs), and the material was denoted RHs-Si@C. Moreover, as an LIB anode, RHs-Si@C exhibited exceptional cycling performance, exemplified by 90.63 % capacity retention at 5 A g−1 over 2000 cycles. Furthermore, the CaH2–AlCl3 reduction system was employed to produce Si nanoparticles (Si NPs) from RHs (R-SiO2, where SiO2 is silica) and from commercial silica (C-SiO2). The R-SiO2-derived Si NPs exhibited a higher residual silicon oxides (SiOx) content than the C-SiO2-derived Si NPs. This was advantageous, as there was sufficient SiOx in the R-SiO2-derived Si NPs to mitigate the volumetric expansion typically associated with Si NPs, resulting in enhanced cycling performance. Impressively, Si NPs were fabricated on a kilogram scale from C-SiO2 in a yield of 82 %, underscoring the scalability of the low-temperature reduction technique.

Construction of Bi2WO6/g-C3N4/Cu foam as 3D Z-scheme photocatalyst for photocatalytic CO2 reduction

Photocatalytic CO2 reduction to hydrocarbon fuels represents a promising solution to CO2 emission challenges. However, photocatalytic CO2 reduction systems face hurdles in practical utilization for the low efficiency of photocatalysts and challenge in catalyst immobilization. Therefore, a novel monolithic three-dimensional Z-scheme photocatalyst was synthesized by fabricating Bi2WO6/g-C3N4 heterojunction on Cu foam substrate (Bi2WO6/g-C3N4/Cu foam) via thermal polymerization and electrophoresis deposition. A series of characterization results, including X-ray diffraction, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, scanning electron microscopy and N2 adsorption–desorption, illustrate the crystalline properties, pore structure, and morphology of the composite photocatalyst. Consequently, Bi2WO6/g-C3N4/Cu foam achieved CO production yield of 33.84 μmol/g cat under visible light illumination for 6 h and retained 96.2 % of initial photocatalytic activity after 30 h of reaction. UV–Vis diffuse reflection spectra, photoluminescence spectra and photoelectrochemical analysis was involved to reveal the mechanism of the photocatalytic activity of composite photocatalyst.The synergistic effect of the Z-scheme mechanism and the hierarchical macroporous structure improves the light absorption, light-induced electron-hole pair separation, and charge transmission. This catalyst construction strategy provides a viable approach for facilitating practical photocatalytic CO2 reduction.

An optimal decision for fresh products' cold chain considering freshness and carbon emission reduction

PurposeThe aim of this study was to analyze the effects of carbon reduction efforts and preservation efforts on system benefits in the cold chain industry of fresh products.Design/methodology/approachThis study develops an optimal decision game model for the fresh products in the cold chain, incorporating the retailer's preservation effort and the supplier's carbon emission reduction effort. It quantifies the relationship between carbon emission reduction effort, preservation effort and system profit. The model considers parameters like carbon trading price, consumer low-carbon preference and consumer freshness preference, reflecting real-world conditions and market trends. Numerical simulations are conducted by varying these parameters to observe their impact on system profit.FindingsUnder the carbon cap-and-trade policy, the profit of the fresh cold chain system is higher than that of the fresh cold chain system without carbon constraints, and the profit of the supplier under decentralized decision-making is increased by nine times in the simulation results. The increase in carbon trading prices can effectively improve the freshness level of fresh products cold chain, carbon emission reduction level and system profit.Originality/valueThis study comprehensively considers the factors of freshness and carbon emission reduction, provides the optimal low-carbon production decision-making reference for the fresh food cold chain and promotes the sustainable development of the fresh food cold chain.

Intelligent robot-assisted fracture reduction system for the treatment of unstable pelvic fractures

BackgroundPrecise and minimally invasive closed reduction is the premise of minimally invasive internal fixation. This paper aims to explore the safety and efficacy of a robot-assisted fracture reduction system (RAFR) in the treatment of pelvic fractures and to analyze its clinical advantages and existing problems.MethodsThe RAFR system intelligently designed the optimal reduction path and target position based on a preoperative three-dimensional(3D) CT scan of the patient. The reduction robotic arm automatically reduced the affected hemipelvis according to the pre-planned reduction path.ResultsThe average residual displacement was the 6.65 ± 3.59 mm. According to Matta’s criteria, there were 7 excellent, 10 good, and 3 fair, and the excellent and good rate was 85%. No postoperative complications occurred.ConclusionIn our study, the RAFR system could complete accurate and minimally invasive closed reduction for most patients with unstable pelvic fractures, which could achieve good fracture reduction quality and short-term efficacy.

Hydra: Generalizing Peephole Optimizations with Program Synthesis

Optimizing compilers rely on peephole optimizations to simplify combinations of instructions and remove redundant instructions. Typically, a new peephole optimization is added when a compiler developer notices an optimization opportunity---a collection of dependent instructions that can be improved---and manually derives a more general rewrite rule that optimizes not only the original code, but also other, similar collections of instructions. In this paper, we present Hydra, a tool that automates the process of generalizing peephole optimizations using a collection of techniques centered on program synthesis. One of the most important problems we have solved is finding a version of each optimization that is independent of the bitwidths of the optimization's inputs (when this version exists). We show that Hydra can generalize 75% of the ungeneralized missed peephole optimizations that LLVM developers have posted to the LLVM project's issue tracker. All of Hydra's generalized peephole optimizations have been formally verified, and furthermore we can automatically turn them into C++ code that is suitable for inclusion in an LLVM pass.

Unlocking high-efficiency decontamination by building a novel heterogeneous catalytic reduction system of thiourea dioxide/biochar

Herein, we reported a new contaminant purification paradigm, which enabled highly efficient reductive denitration and dechlorination using a green, stable reducing agent thiourea dioxide (TDO) coupled with biochar (BC) over a wide pH range under anoxic conditions. Specifically, BC acted as both activators and electron shuttles for TDO decomposition to achieve complete anoxic degradation of p-nitrophenol (PNP), p-nitroaniline, 4-chlorophenol and 2,4-dichlorophenol within 2 h. During this process, multiple strongly reducing species (i.e., SO22-, SO2•- and e-/H•) were generated in BC/TDO systems, accounting for 13.3%, 9.7% and 75.5% of PNP removal, respectively. While electron transfer between TDO and H+ or contaminants mediated by BC led to H• generation and contaminant reduction. These processes depended on the electron-accepting capacity and electron-conducting domains of biochar. Significantly, the BC/TDO systems were highly efficient at a pH of 2.0–8.0, especially under acidic conditions, which performed robustly in common natural water constituents.

A Bayesian network development methodology for fault analysis; case study of the automotive aftertreatment system

This paper proposes a structured methodology for generating a Bayesian network (BN) structure for an engineered system and investigates the impact of integrating engineering analysis with a data-driven methodology for fault analysis. The approach differs from the state of the art by using different initial information to build the BN structure. This method identifies the cause-and-effect relationships in a system by Causal Loop Diagram (CLD) and based on that, builds the Bayesian Network structure for the system. One of the challenges in identifying the root cause for a fault is to determine the way in which the related variable causes the fault. To deal with this challenge, the proposed methodology exploits Dynamic Fault Tree Analysis (DFTA), CLD and the correlation between variables. To demonstrate and evaluate the effectiveness of the presented method, it is implemented on the data-driven methodology applied to the automotive Selective Catalytic Reduction (SCR) system and the obtained results have been compared and discussed. The proposed methodology offers a comprehensive approach to build a BN structure for an engineered system, which can enhance the system's reliability analysis.

Analysis of the Dynamics of a Cubic Nonlinear Five-Dimensional Memristive Chaotic System and the Study of Reduced-Dimensional Synchronous Masking

To improve the complexity of the chaotic system and achieve the effective transmission of image information, in this paper, a five-dimensional memristive chaotic system with cubic nonlinear terms is constructed, which has four pairs of symmetric coordinates. First, the cubic nonlinear memristive chaotic system is analyzed using the Lyapunov exponential map, bifurcation map, and attractor phase diagram. The experimental results show that under four pairs of symmetric coordinates, the system exists not only parameter-dependent symmetric rotational coexisting attractor and transient chaotic phenomena but also exists super-multistationary with alternating chaotic cycles dependent on the initial value of the memristor. Then, it is proposed to add a constant term to the linear state variable to explore the effect of the offset increment of the linear state variable on the system in four pairs of symmetric coordinates, while circuit simulation of the five-dimensional chaotic system is carried out using Simulink to verify its existence and realisability. Finally, the synchronization of the dimensionality reduction system and the confidential transmission of the image are achieved, using the control voltage of the system to replace the internal state variables of the memristor to achieve the one-dimensional reduction process, and an adaptive synchronization controller is designed to synchronize the system before and after the dimensionality reduction. Based on the above, an image to be transmitted is modulated into a one-dimensional array and then subjected to the fractional and cyclic operations and combined with the linear encryption and decryption functions and the chaotic masking technique, the simple encryption and decryption of the image processes are realized.

Integration of Electric Vehicles and Renewable Energy in Indonesia’s Electrical Grid

As the global transition toward sustainable energy gains momentum, integrating electric vehicles (EVs), energy storage, and renewable energy sources has become a pivotal strategy. This paper analyses the interplay between EVs, energy storage, and renewable energy integration with Indonesia’s grid as a test case. A comprehensive energy system modeling approach using PLEXOS is presented, using historical data on electricity generation, hourly demand, and renewable energy, and multiple scenarios of charging patterns and EV adoption. Through a series of scenarios, we evaluate the impact of different charging strategies and EV penetration levels on generation capacity, battery storage requirements, total system cost, renewable energy penetration, and emissions reduction. The findings reveal that optimized charging patterns and higher EV adoption rates, compared to no EVs adoption, led to substantial improvements in renewable energy utilization (+4%), emissions reduction (−12.8%), and overall system cost (−9%). While EVs contribute to reduced emissions compared to conventional vehicles, non-optimized charging behavior may lead to higher total emissions when compared to scenarios without EVs. The research also found the potential of vehicle to grid (V2G) to reduce the need for battery storage compared to zero EV (−84%), to reduce emissions significantly (−23.7%), and boost penetration of renewable energy (+10%). This research offers valuable insights for policymakers, energy planners, and stakeholders seeking to leverage the synergies between EVs and renewable energy integration to pursue a sustainable energy future for Indonesia.

Using traditional knowledge to reduce disaster risk - A case of Tibetans in Deqen County, Yunnan Province

Traditional Knowledge (TK) is practical knowledge and expertise that is accumulated over generations by individuals living within a specific environment, and transmitted through tradition. This study offers a systematic review of the current state of research on TK in Disaster Risk Reduction (DRR) and establishes a DRR framework, based on a comprehensive survey of Tibetan communities in Deqen County, Yunnan Province, from 2003 to 2022. Specifically, the study considers the cooperation between local Tibetan residents with multiple parties in leveraging their unique traditional knowledge to mitigate disaster risks. To evaluate the efficacy of traditional knowledge and multiparty cooperation in disaster risk reduction actions, the research employs a range of methodologies, including quantitative analysis, participatory surveys, semi-structured interviews, and literature research. This case serves as a valuable reference point for developing a multi-disaster reduction system and may be aligned with the Sendai Framework's guidelines, demonstrating that traditional knowledge plays a crucial role in assisting local communities to cope with natural disasters.

Techno-Economic Evaluation of Direct Low-Pressure Selective Catalytic Reduction for Boil-Off Gas Treatment Systems of NH3-Fueled Ships

This study proposes a feasible solution for boil-off gas (BOG) treatment to facilitate NH3 fuel use by ocean-going ships, which is currently considered an alternative fuel for ships. Two systems were designed and analyzed for BOG in IMO Type-A NH3 fuel storage tanks for 14,000 TEU container ships. First, BOG lost inside the storage tank minimized economic losses through the onboard re-liquefaction system. The total energy consumed by the system to process NH3 gas generated in the fuel tank at 232.4 kg/h was 51.9 kW, and the specific energy consumption (SEC) was 0.223 kWh/kg. Second, NH3 was supplied to the direct Low-Pressure Selective Catalytic Reduction (LP-SCR) system to treat marine pollutants generated by combustion engines. The feasible design point was determined by calculating the NH3 feed flow rate using three methodologies. The energy consumed by the direct LP-SCR system was 3.89 and 2.39 kW, and the SEC was 0.0144 at 0.0167 kWh/kg at 100% and 25% load, respectively. The feasibility was indicated via economic analysis. Depending on the life cycle cost, the competitiveness of the re-liquefaction system depends on the price of NH3, where a higher price yields a more economical solution. In conclusion, the direct LP-SCR system has a low overall cost because of its low energy consumption when supplying NH3 and its reduced amount of core equipment.

Ammonia coverage ratio control of a novel two-cell SCR-DeNOX system configuration based on IA-ISMC

To respond the China’s “14th Five-Year Plan” on the control of nitrogen oxides (NOX) emission, urea-based selective catalytic reduction (SCR) system has been widely applied to reduce the NOX emission from the diesel engine. NO2 is no longer a factor to be ignored while refining the SCR-DeNOX system model because of the ship diesel engine's long-term low temperature and oxygen-rich condition, which provides abundant conditions for the creation of NO2. Therefore, a refined eight-state two-cell SCR-DeNOX model is established in this paper. Meanwhile, the trade-off between NOX emission and tailpipe ammonia (NH3) slip is one of the major challenges which SCR-DeNOX system is facing. While meeting NOX emission standards, the requirement of limiting NH3 slip to prevent secondary pollution is becoming increasingly urgent, which needs a better structure or controller. Therefore, a two-cell SCR-DeNOX system with a by-pass valve in front of the NH3 injection is designed, integral sliding mode control based on inversion algorithm (IA_ISMC) is proposed for each cell. Based on the FTP-75 test cycle, there are three points of view are presented. Firstly, compared with the traditional six-state model, simulation results from the refined eight-state SCR-DeNOX model are closer to the experimental data. Secondly, the introduction of the by-pass structure has a mild impact on the NOX conversion efficiency, but can largely limit the NH3 slip. Finally, the controller based on IA_ISMC effectively improves the tracking performance of NH3 coverage ratio and reduces the cost of NH3 injection. To sum up, the refined two-cell SCR-DeNOX system with a by-pass valve based on IA_ISMC can enhance SCR performance and lower costs.

A Rule-based Approach to English-Okun Prepositional Phrase Machine Translation

Okun culture is gradually going into extinction because the language is greatly dominated by English language. Therefore, this research developed a rule-based English-Okun machine translator using prepositional phrase. The dataset used were obtained from locally spoken words and the correctness of the re-write rules was tested using Java Formal Language Automata Package. Human judgment was employed in evaluating the system based on orthography accuracy. Results show that the developed translator is 95 percent accurate while experimental subject respondents have an accuracy of 58 percent. The developed machine translator’s performance is closer to the Experts’ but higher than that of the experimental subject respondents, this shows that indigenous people are not good at writing Okun language and find it hard to separate the dialect from Yoruba language. Hence, research in EnglishOkun machine translation should be intensified in order to prevent the language from going into extinction and future research should consider extending the full form bilingual lexicon of Okun language to achieve improved accuracy.